Author:
Irie Kota, ,Takahashi Masahito,Terabayashi Kenji,Ogishima Hidetoshi,Umeda Kazunori, ,
Abstract
This paper proposes skin color registration using the recognition of waving hands. In order to recognize hand gestures from images, skin colors are useful information. The proposed method can register skin colors simply and quickly because it uses just a few waves of the hand. The method consists of 2 steps. First, the regions of the waving hands are extracted from low-resolution images without using color information. Second, the color values of the extracted regions are classified into background colors and hand colors depending on time series of color images. The color information classified as hand colors is registered as skin colors. The proposed method is robust against lighting conditions and individual differences in skin color, because the skin color is registered as an adapted skin color in each case. Several experiments are conducted to demonstrate the effectiveness of the proposed method.
Publisher
Fuji Technology Press Ltd.
Subject
Electrical and Electronic Engineering,General Computer Science
Reference22 articles.
1. V. Pavlovic, R. Sharma, and T. Huang, “Visual Interpretation of Hand Gestures for Human-Computer Interaction: A Review,” IEEE Trans. on Pattern Analysis and Machine Intelligence (PAMI), Vol.19, No.7, pp. 677-695, 1997.
2. J. Sherrah and S. Gong, “VIGOUR: A System for Tracking and Recognition of Multiple People and their Activities,” Proc. of the Int. Conf. on Pattern Recognition, pp. 179-183, 2000.
3. P. Hong, M. Turk, and T. S. Huang, “Gesture Modeling and Recognition Using Finite State Machines,” IEEE Int. Conf. on Automatic Face and Gesture Recognition, pp. 691-694, 2000.
4. H. Wu, T. Shioyama, and H. Kobayashi, “Spotting Recognition of Head Gestures from Color Image Series,” Proc. of the Int. Conf. on Pattern Recognition, pp. 83-85, 1998.
5. A. Nishikawa, A. Ohnishi, M. Nishimura, A. Hirano, K. Koara, and F. Miyazaki, “Systematic selection of local correlation parameters for opticalflow-based gesture recognition,” Proc. of the 8th IEEE Int. Workshop on Robot and Human Interaction (ROMAN’99), pp. 183-188, 1999.